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» The Geodesic Self-Organizing Map and Its Error Analysis
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ACSC
2005
IEEE
13 years 10 months ago
The Geodesic Self-Organizing Map and Its Error Analysis
The Self-Organizing Map (SOM) is one of the popular Artificial Neural Networks which is a useful in clustering and visualizing complex high dimensional data. Conventional SOMs are...
Yingxin Wu, Masahiro Takatsuka
DMIN
2008
190views Data Mining» more  DMIN 2008»
13 years 6 months ago
Optimization of Self-Organizing Maps Ensemble in Prediction
The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...
Elie Prudhomme, Stéphane Lallich
DATAMINE
2010
120views more  DATAMINE 2010»
13 years 5 months ago
A weighted voting summarization of SOM ensembles
Abstract Weighted Voting Superposition (WeVoS) is a novel summarization algorithm for the results of an ensemble of Self-Organizing Maps. Its principal aim is to achieve the lowest...
Bruno Baruque, Emilio Corchado
CIBCB
2005
IEEE
13 years 10 months ago
Toward Protein Structure Analysis with Self-Organizing Maps
- Establishing structure-function relationships on the proteomic scale is a unique challenge faced by bioinformatics and molecular biosciences. Large protein families represent nat...
Lutz Hamel, Gongqin Sun, Jing Zhang
IJCNN
2000
IEEE
13 years 9 months ago
EM Algorithms for Self-Organizing Maps
eresting web-available abstracts and papers on clustering: An Analysis of Recent Work on Clustering Algorithms (1999), Daniel Fasulo : This paper describes four recent papers on cl...
Tom Heskes, Jan-Joost Spanjers, Wim Wiegerinck